Desarrollo de herramientas computacionales para la planificación operativa de corto plazo de sistemas eléctricos de potencia en base a técnicas heurísticas : Herramienta computacional para la planificación operativa de corto plazo de sistemas eléctricos de potencia en base al algoritmo de enjambre de partículas.

Abstract

In this degree Work, a computational tool is developed in Python programming language that allows solving the problem of short-term hydrothermal operational planning of electrical power systems based on the heuristic technique of particle swarm optimization (PSO). The developed tool optimizes the daily operating cost associated with the operation, start-up and shutdown of the thermoelectric generators present in an electrical power system. The electrical system is considered to have single-node power, that is, all power generation is intended to cover demand, without considering the losses generated in the transmission system. To reduce the complexity of the mathematical modeling of the problem, a linear approximation was considered in the cost functions of the thermal units. The computational tool is tested with the implementation of the IEEE 14-BUS and IEEE 39-BUS systems, obtaining the power generated by each electric unit of generation throughout the period of analysis, as well as the associated generation operating cost of the system. power. Finally, the results were contrasted with the heuristic techniques by genetic algorithms (GA) and gray wolf optimization (GWO), which were developed as components of this project.